Turning Biological Complexity into R&D Advantage with Virtual Cells - with Giorgio Gaglia of Sanofi & Daniel Veres of Turbine

Drug discovery teams are running short of new ideas to test, and AI models that simulate how cells respond to drugs only pay off once leaders know when those predictions can be trusted with experiments, timelines, and budget.   In this episode, Daniel Veres, Co-Founder and Chief Scientific Officer at Turbine, and Giorgio Gaglia, Head of Systems and Disease Biology at Sanofi, examine with host Yolandi de Weerdt how testing models on data they have never seen shows which R&D decisions their predictions can reliably inform.   The discussion offers R&D leaders a practical way to judge when a model's predictions are ready to inform which experiments to run, where in the pipeline to start, and how much risk to accept.   This episode is sponsored by Turbine.   Learn how these conversations drive pipeline for other AI brands — download our media kit at emerj.com/AD1

In biopharma R&D, AI investment has overwhelmingly targeted generating more drug candidates, even though the industry has rarely lacked for compounds worth pursuing. In this episode, Mukhtar Ahmed, Director of Project and Portfolio Strategy at Greenstone Biosciences, explores why the harder and more valuable problem is deciding which candidates deserve continued capital and attention. The conversation covers synthesizing fragmented evidence across teams, keeping human judgment and accountability in the loop, and measuring AI's impact across a portfolio rather than a single program. ​ Emerj works with a select group of AI vendors to reach Fortune 500 decision-makers through research, media, and direct access. If you want to be considered, download our media kit at emerj.com/AD1

Finance teams face immense pressure to operate faster, but rushing to automate over fragmented systems only compounds errors downstream. Ciprian Porutiu, SVP of Strategic Initiatives at Marsh, joins host Yolandi de Weerdt to explain why establishing a common language and federated data domains matters far more than forcing everything into a single centralized database. He shares practical approaches for managing phased rollouts, involving cross-functional users early in system design, and connecting underlying data governance directly to strategic business performance. ​ This episode is sponsored by Fynapse. Learn how financial institutions are digitizing paper-based records to unlock usable data for AI, and using alternative data like public web and social signals to enhance risk assessment, download our free PDF report, "AI in Financial Services Executive Cheat Sheet" at emerj.com/fcs1

For large banks, the barrier to AI at scale is rarely the model. It's decades of fragmented systems, inherited through mergers, acquisitions, and new products, where each team trusts its own data and no single view of context exists. Agentic AI doesn't fix that fragmentation; it amplifies it across every user and every prompt. ​ In this episode, Nathaniel Bell, Data Management Director at Wells Fargo, joins host Yolandi de Weerdt,  to examine why the real challenge for regulated institutions is scaling trust while automating, why leaders should judge new technology on the business outcome it can prove rather than the demo, and why no process should be automated before it's standardized. ​ Bell outlines the practical shifts underway: from manual attestations and spreadsheets toward automated logs that show what happened in a workflow, from governance as document review toward governance built into workflows as code, and from buying new tools toward changing how teams work once they have them. ​ According to Nielsen, 91% of podcast listening happens alone, indicating deep, undistracted attention — ideal for complex B2B messaging. ​ To learn how leading brands and AI startups connect with enterprise AI buyer audiences at scale, download our media kit at emerj.com/AD1

Hospitals and clinics continue to face a central challenge: extensive cardiac testing still fails to deliver clear, consistent diagnostic answers, slowing decision‑making and creating downstream operational and financial strain. In this episode, Jim Hartman, Chief Commercial Officer at Cleerly, examines with host Marilie Fouché how AI‑driven coronary CTA analysis strengthens diagnostic certainty, streamlines workflows across radiology, cardiology, and the cath lab, and supports more defensible adoption decisions for clinical and operational leaders. The discussion highlights practical evaluation criteria — clinical impact, workflow efficiency, and financial return — that executives can use to assess whether advanced imaging technologies can be integrated and scaled within their organizations. This episode is sponsored by Cleerly. ​ Learn how to identify AI trends by tracking where venture funding is flowing, and by listening to how leading CEOs describe risk and competitive strategy, download our free PDF report, "3 Ways to Discover AI Trends in Any Sector" at emerj.com/ait1  

For consumer goods companies, the gap between the commercial plan agreed at head office and what gets executed on the shelf is one of the costliest disconnects in the business — investment goes out against activity that never happens, and revenue never arrives against activity that does. ​ In this episode, Stephanie Lilley, VP of Transformation for Europe at Reckitt, examines why rigid rep call cycles and fragmented store-level data keep that gap open, and where AI is starting to close it — from image recognition that verifies in-store compliance to dynamic routing that sends field teams to the stores with the highest return — with host Daniel Faggella, Emerj CEO and Head of Research. ​ She outlines the practical shifts underway: from fixed call files toward a mix of core relationship stores and flexible, ROI-driven visits, from full-time field coverage toward crowdsourced compliance checks, and from geography as the deciding factor toward the quality and recency of store-level data. ​ Learn how these conversations drive pipeline for AI brands — download our media kit at emerj.com/AD1

Traditional, event-based training can't keep pace with technical skills that now shift every six to twelve months. ​ In this episode, Nicola Lyons, Senior Director of Talent Operations at Andela, breaks down why assessment-based, personalized learning is replacing one-time training programs. ​ The conversation covers how leaders can build continuous learning loops that keep technical teams current without turning into another mandatory course. ​ This episode is sponsored by Andela. ​ Reach VP+ leaders at America's largest enterprises through Emerj's podcasts. Emerj reaches 1 million listeners annually. Learn how AI brands use Emerj to generate leads: emerj.com/AD1

Generative AI is entering clinical workflows just as healthcare institutions grapple with black-box outputs, unclear regulation, and the need for provable accuracy.   In this episode, Rhett Alden, CTO at Elsevier, joins Emerj's Yolandi de Weerdt to articulate how claim-level validation and transparent sourcing are becoming prerequisites for clinical trust in AI. The conversation covers emerging AI governance boards modeled on clinical trial review structures, the limits of current US regulation, and why final clinical responsibility remains with the physician. Learn the strategies Emerj uses to help leading AI brands and startups connect with their ideal enterprise AI buyers: emerj.com/AD1    

For AI systems built into vehicles, robots, and industrial equipment, being smart isn't enough — the difference between success and failure often comes down to whether real-time performance was designed in from the start or added on afterward. In this episode, Drew Barbier, Vice President, IP Business Unit at MIPS, breaks down why starting with the software workload, rather than the hardware, produces measurably better outcomes in real-time compute design. The conversation covers a real-world example of a three-to-five-times performance gain from workload-first design, what changes on a team's side when real-time becomes a starting requirement instead of an afterthought, and how leaders can tell within six months whether their approach is working. This episode is sponsored by MIPS. Learn how to structure landing pages for higher conversion, and how to use self-qualification systems to prioritize high-intent leads. Download our free PDF report, "B2B AI Lead Generation Guide," at emerj.com/aig1  

Enterprise sales teams routinely let the majority of inbound leads go untouched simply because there isn't enough team bandwidth to work them all. In this episode, Vanessa Tabbert, VP of Agentic Transformation and Sales Development at Salesforce, breaks down how her own team deployed an AI SDR agent to recover leads that would otherwise go cold, without replacing the humans who convert the best ones. The conversation covers how to identify a low-risk first use case, why an AI agent should be coached and measured like a team member rather than launched and left alone, and how the same approach scales down to a small SMB sales team. This episode is sponsored by Salesforce. ​ To learn the exact strategies we use to help leading AI brands and startups connect with their ideal enterprise AI buyers, visit: emerj.com/AD1